Natural products in cancer therapy: Past, present and future

M Huang, JJ Lu, J Ding - Natural products and bioprospecting, 2021 - Springer
Natural products, with remarkable chemical diversity, have been extensively investigated for
their anticancer potential for more than a half-century. The collective efforts of the community …

Application of artificial intelligence in medicine: an overview

P Liu, L Lu, J Zhang, T Huo, S Liu, Z Ye - Current medical science, 2021 - Springer
Artificial intelligence (AI) is a new technical discipline that uses computer technology to
research and develop the theory, method, technique, and application system for the …

Demystifying supervised learning in healthcare 4.0: A new reality of transforming diagnostic medicine

S Roy, T Meena, SJ Lim - Diagnostics, 2022 - mdpi.com
The global healthcare sector continues to grow rapidly and is reflected as one of the fastest-
growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare …

Advances in targeting the WNT/β-catenin signaling pathway in cancer

A Chatterjee, S Paul, B Bisht, S Bhattacharya… - Drug Discovery …, 2022 - Elsevier
WNT/β-catenin signaling orchestrates various physiological processes, including embryonic
development, growth, tissue homeostasis, and regeneration. Abnormal WNT/β-catenin …

Machine learning approaches and their applications in drug discovery and design

S Priya, G Tripathi, DB Singh, P Jain… - Chemical Biology & …, 2022 - Wiley Online Library
This review is focused on several machine learning approaches used in chemoinformatics.
Machine learning approaches provide tools and algorithms to improve drug discovery. Many …

Machine learning and deep learning in data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry

SA Kumar, TD Ananda Kumar… - Future Medicinal …, 2022 - Taylor & Francis
Predicting novel small molecule bioactivities for the target deconvolution, hit-to-lead
optimization in drug discovery research, requires molecular representation. Previous reports …

Impact of artificial intelligence on compound discovery, design, and synthesis

F Miljković, R Rodríguez-Pérez, J Bajorath - ACS omega, 2021 - ACS Publications
As in other areas, artificial intelligence (AI) is heavily promoted in different scientific fields,
including chemistry. Although chemistry traditionally tends to be a conservative field and …

Artificial intelligence and machine learning for lead-to-candidate decision-making and beyond

D McNair - Annual review of pharmacology and toxicology, 2023 - annualreviews.org
The use of artificial intelligence (AI) and machine learning (ML) in pharmaceutical research
and development has to date focused on research: target identification; docking-, fragment …

Feature importance correlation from machine learning indicates functional relationships between proteins and similar compound binding characteristics

R Rodríguez-Pérez, J Bajorath - Scientific reports, 2021 - nature.com
Abstract Machine learning is widely applied in drug discovery research to predict molecular
properties and aid in the identification of active compounds. Herein, we introduce a new …

Review of predicting synergistic drug combinations

Y Pan, H Ren, L Lan, Y Li, T Huang - Life, 2023 - mdpi.com
The prediction of drug combinations is of great clinical significance. In many diseases, such
as high blood pressure, diabetes, and stomach ulcers, the simultaneous use of two or more …